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1st International Symposium on Combinatorial Optimization (ISCO)

作者： Gabrel, V. Lacroix, M. Murat, C. Remli, N. Univ Paris 09 Lamsade F-75775 Paris 16 France

In robust optimization, the multi-stage context (or dynamic decision-making) assumes that the information is revealed in stages. So, part of the decisions must be taken before knowing the real values of the uncertain parameters, and another part, called recourse decisions, is taken when the information is known. In this paper, we are interested in a robust version of the location transportation problem with an uncertain demand using a 2-stage formulation. The obtained robust formulation is a convex (not linear) program, and we apply a cutting plane algorithm to exactly solve the problem. At each iteration, we have to solve an NPhard recourse problem in an exact way, which is time-consuming. Here, we go further in the analysis of the recourse problem of the location transportation problem. In particular, we propose a mixed integer program formulation to solve the quadratic recourse problem and we define a tight bound for this reformulation. We present an extensive computation analysis of the 2-stage robust location transportation problem. The proposed tight bound allows us to solve large size instances. (c) 2011 Elsevier B.V. All rights reserved.

关键词： Robust optimization Interval uncertainty Convex optimization mixed integer linear programming Location transportation problem

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A Comparative Analysis of Energy Storage and N-1 Network Security in Transmission Expansion Planning

A Comparative Analysis of Energy Storage and N-1 Network Sec...

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International Universities Power Engineering Conference

作者： E. B. Obio J. Mutale The University Of Manchester

ISBN: (纸本)9781467396578

In a restructured power system, one of the key objectives of transmission network expansion is to provide nondiscriminatory access to cheaper generation for all consumers. However, the robustness of the transmission network against all uncertainties such as credible contingencies should equally be maintained. Thus the development of effective methodologies and strategies to satisfy this objective is a major challenge faced by the transmission expansion planners in the new environment. In this paper a static transmission expansion model with energy storage is proposed. The energy storage is coordinated with transmission expansion planning in a system with base load generators and expensive peaking power plants. The energy storage is modelled to store the cheaper generation from the base load power plants at off peak periods and discharges to meet the demand at peak periods. Four distinct transmission expansion models with and without energy storage system (ESS) and N-1 network security constraint are developed for the comparative analysis. The whole problem is formulated as a mixed integer linear programming (MILP) problem with the objective of minimizing the operational cost of the generators as well as the transmission line and storage investment costs over several demand levels. The proposed methodology is demonstrated on the IEEE 24 bus reliability test system (RTS). The overall results from the model showed that energy storage benefits the system by deferring investment in transmission lines. The model also confirmed that the marginal benefit of storage diminishes as the investment in ESS increases. In addition, the economic viability of corrective planning over preventive planning of transmission network is also justified.

关键词： Comparative analysis Energy storage mixed integer linear programming N-1 network security Transmission investment Transmission expansion planning

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European Market Coupling Algorithm incorporating clearing conditions of block and complex orders

European Market Coupling Algorithm incorporating clearing co...

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IEEE Eindhoven PowerTech Conference

作者： Grigoris A. Dourbois Pandelis N. Biskas Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece

In this paper an algorithm for the solution of the European electricity market coupling is presented, considering all block and complex orders available in the European Power Exchanges. The model takes into account the clearing conditions of profile and regular block orders, linked block orders, exclusive group of block orders and flexible hourly orders, as well as the clearing conditions of Minimum Income Condition and Load Gradient orders, possibly under a scheduled stop condition. The model considers also hourly flow ramping constraints on single interconnections or group of interconnections, net position ramping constraints, interconnection losses and tariffs. The flow-based approach is implemented, using the zonal PTDF matrix. The algorithm eliminates possible paradoxically accepted block and MIC orders within an iterative process. The proposed algorithm is evaluated in a pan-European day-ahead electricity marketplace.

关键词： European electricity market Block and complex orders Iterative algorithm mixed integer linear programming

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Market clearing model for microgrids with probabilistic reserve

Market clearing model for microgrids with probabilistic rese...

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IEEE Eindhoven PowerTech Conference

作者： Luis E. Luna Horacio Torres Andres Pavas Department of Electrical and Electronic Engineering National University of Colombia Bogotá Colombia

This paper proposes an energy-reserve market clearing model for microgrids which considers a probability reserve criteria. The probabilistic reserve criteria include pre-selected scenarios associated to the unreliability of generators and uncertainties caused by loads and renewable units. Unlike traditional deterministic reserve-constrained market clearing models, this paper determines the optimal amount of reserve as the point in which the sum of its operating costs and the expected cost of load shed reach a minimum. The proposed model is formulated as a stochastic programming problem oriented to co-optimize two electricity markets. The first market is the hour-ahead which evaluate the unit commitment and the energy-reserve scheduling before the realization of scenarios in the microgrid. The second is the balancing market that investigates the security assurance in the pre-selected scenarios of the microgrid. An energy management procedure was developed in order to implement the stochastic programming problem on the real microgrid ATENEA. From this, it was concluded that the reserve capacity of the microgrid throughout the scheduling horizon mainly varies according to the power output of renewable units.

关键词： Market clearing Microgrids mixed integer linear programming Probabilistic security Reserve Stochastic programming

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System Load Margin Evaluation using mixed-integer Conic Optimization

System Load Margin Evaluation using Mixed-Integer Conic Opti...

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North American Power Symposium

作者： Xin Fang Fangxing Li Qinran Hu Ningchao Gao Dept. of EECS Univ. of Tennessee Knoxville TN USA

ISBN: (纸本)9781467373906

This paper proposes a mixed-integer conic optimization approach for estimating system load margin to evaluate static voltage stability in transmission networks. The proposed problem formulation employs the conic quadratic format of power flow equations, and then utilizes a polyhedral approximation to transform the conic quadratic constraints to linear constraints. Also, the complementary constraint of generators' reactive power limit has been considered. The numerical case studies have been performed on IEEE 14, 30, 39 and 118 bus systems, and validated that the proposed method is an effective tool for system load margin evaluation.

关键词： Static voltage stability Load margin Conic optimization mixed integer linear programming

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LARGE-SCALE EVACUATION NETWORK MODEL FOR TRANSPORTING EVACUEES WITH MULTIPLE PRIORITIES

LARGE-SCALE EVACUATION NETWORK MODEL FOR TRANSPORTING EVACUE...

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作者： HYEONG SUK NA Texas A&M University

学位级别：硕士

There are increasing numbers of natural disasters occurring worldwide, particularly in populated areas. Such events affect a large number of people causing injuries and fatalities. With ever increasing damage being caused by large-scale natural disasters, the need for appropriate evacuation strategies has grown dramatically. Providing rapid medical treatment is of utmost importance in such circumstances. The problem of transporting patients to medical facilities is a subject of research that has been studied to some extent. One of the challenges is to find a strategy that can maximize the number of survivors and minimize the total cost simultaneously under a given set of resources and geographic constraints. However, some existing mathematical programming methodologies cannot be applied effectively to such large-scale problems. In this thesis, two mathematical optimization models are proposed for abating the extensive damage and tragic impact by large-scale natural disasters. First of all, a mathematical optimization model called Triage-Assignment-Transportation (TAT) model is suggested in order to decide on the tactical routing assignment of several classes of evacuation vehicles between staging areas and shelters in the nearby area. The model takes into account the severity level of the evacuees, the evacuation vehicles' capacities, and available resources of each shelter. TAT is a mixed-integer linear programming (MILP) and minimum-cost flow problem. Comprehensive computational experiments are performed to examine the applicability and extensibility of the TAT model. Secondly, a MILP model is addressed to solve the large-scale evacuation network problem with multi-priorities evacuees, multiple vehicle types, and multiple candidate shelters. An exact solution approach based on modified Benders' decomposition is proposed for seeking relevant evacuation routes. A geographical methodology for a more realistic initial parameter setting is developed by employing spatia

关键词： Large-scale optimization model modified Benders’ decomposition natural disaster evacuation plan geographic information system mixed integer linear programming Thesis

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A 43-level filterless CMLI with very low harmonics values

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Journal of Electrical Systems and Information Technology 2014年第3期1卷 175-186页

作者： Mahmoud El-Bakry Electronics Research Institute Egypt

This paper introduces a 43-level asymmetric uniform step cascaded multilevel inverter (CMLI) that consists of four H-bridges per phase, with different dc sources of values E, 2E, 7E and 11E. A mixed integer linear programming (MILP) optimization model is applied to determine the switching angles of the CMLI power switches that can minimize the values of any undesired harmonics. Single phase and three phase cases are considered. The results show very low values of all the undesired harmonics over wide voltage ranges, which agree with the IEEE standards 519-1992 for voltage distortion limits for both the values of %THDE and % V Hmax so that no output filters are needed.

关键词： Asymmetric cascaded multilevel inverters Exact total harmonic distortion Harmonic values minimization IEEE standards for electrical power systems mixed integer linear programming

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Optimal placement of capacitors in a radial network using conic and mixed integer linear programming

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ELECTRIC POWER SYSTEMS RESEARCH 2008年第6期78卷 941-948页

作者： Jabr, R. A. Notre Dame Univ Elect Comp & Commun Engn Dept Zouk Mosbeh Lebanon

This paper considers the problem of optimally placing fixed and switched type capacitors in a radial distribution network. The aim of this problem is to minimize the costs associated with capacitor banks, peak power, and energy losses whilst satisfying a pre-specified set of physical and technical constraints. The proposed solution is obtained using a two-phase approach. In phase-I, the problem is formulated as a conic program in which all nodes are candidates for placement of capacitor banks whose sizes are considered as continuous variables. A global solution of the phase-I problem is obtained using an interior-point based conic programming solver. Phase-II seeks a practical optimal solution by considering capacitor sizes as discrete variables. The problem in this phase is formulated as a mixed integer linear program based on minimizing the L1-norm of deviations from the phase-I state variable values. The solution to the phase-II problem is obtained using a mixed integer linear programming solver. The proposed method is validated via extensive comparisons with previously published results. (C) 2007 Elsevier B.V. All rights reserved.

关键词： capacitor compensated distribution lines mixed integer linear programming nonlinear programming optimization methods reactive power control

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A Polyhedral Study for Delay Management in Public Transportation

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Procedia - Social and Behavioral Sciences 2014年 108卷 15-25页

作者： Luigi De Giovanni Géraldine Heilporn Martine Labbé Dipartimento di Matematica - Università degli Studi di Padova via Trieste 63 35121 Padova Italy GOM Université Libre de Bruxelles Bd du Triomphe CP210/01 1050 Bruxelles Belgium

The attractiveness of intermodal public transportation networks is strongly related to the reliability of connections between vehicles. As a consequence, operational decisions are required to manage connections in case of unpredictable events like breakdowns or vehicle delays. In such cases, the network operators have to determine if connected vehicles should wait for the delayed ones or keep their schedule. The Delay Management Problem (DMP) consists in defining a wait/depart policy that minimizes the total delay incurred by passengers. In this work we present a polyhedral study for DMP: starting from a previous integer linear programming formulation and from results on the mixed 0-1 Knapsack Polytope, we derive new valid inequalities and we show that they define facets of the convex-hull of some special cases.

关键词： Delay Management mixed integer linear programming Polyhedral Study Valid Inequalities

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Finding the Best Sink Location in WSNs with Reliability Route Analysis

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Procedia Computer Science 2014年 32卷 1160-1167页

作者： Marwa M. Hassan Rabie A. Ramadan Hatem M. El Boghdadi Teaching Assistant Faculty of Engineering- Cairo University Giza and 12613 Egypt Lecturer Faculty of Engineering- Cairo University Giza and 12613 Egypt Associate professor Faculty of Engineering- Cairo University Giza and 12613 Egypt

Wireless Sensor Network (WSN) became one of the emerged networks that are used in many critical applications. One of the challenges of the network is the energy source of its sensors since sensors depends, in most of the cases, on a double AA batteries and they are supposed to live for long time. One of the important methods to save sensors energy is to reduce the messages ﬂow transferred to the sink node in a multi-hop wireless sensor networks. To do so, this paper investigates the best location to the sink node to maximize the reliability of a message delivery before it is being received and processed by a sink. The paper introduces the optimal location solution through utilizing the mixed integer linear programming (MILP) solution to the problem in small- scale WSNs. Consequently, maximum reliability of a path may lead to the minimum energy consumed for retransmission along the routing path. However, in large-scale networks, the paper introduces the Genetic Algorithm (GA) as one of the heuristics solution. The Fitness function of the GA calculates the negative value of the log of the reliability of a path and the GA tries to ﬁnd the sink position with the minimum ﬁtness value to minimize the energy spent by each sensor in the routing towards the sink. An extensive set of experiments are introduced and the MILP solution results are compared to GA approach for the GA performance measure. The comparison showed that the GA have found near optimal solution in reasonable time. In addition, GA is utilized in large-scale problems as well.

关键词： Genetic Algorithm mixed integer linear programming sink location reliability routing wireless sensor networks.

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